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2. You are given a supervised data set with 10 binary features and one more feature with 10,000 categories (representing cities in the U.S.). You
2. You are given a supervised data set with 10 binary features and one more feature with 10,000 categories (representing cities in the U.S.). You have only 500 examples to train a neural network. Give one suggestion to preprocess this data set, so that you could train a neural network without the risk of overfitting? Based on your solution, how many inputs will your neural network have?
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